'''DEFINITION''' We have derived an annual eutrophication and eutrophication indicator map for the North Atlantic Ocean using satellite-derived chlorophyll concentration. Using the satellite-derived chlorophyll products distributed in the regional North Atlantic CMEMS MY Ocean Colour dataset (OC- CCI), we derived P90 and P10 daily climatologies. The time period selected for the climatology was 1998-2017. For a given pixel, P90 and P10 were defined as dynamic thresholds such as 90% of the 1998-2017 chlorophyll values for that pixel were below the P90 value, and 10% of the chlorophyll values were below the P10 value. To minimise the effect of gaps in the data in the computation of these P90 and P10 climatological values, we imposed a threshold of 25% valid data for the daily climatology. For the 20-year 1998-2017 climatology this means that, for a given pixel and day of the year, at least 5 years must contain valid data for the resulting climatological value to be considered significant. Pixels where the minimum data requirements were met were not considered in further calculations. We compared every valid daily observation over 2021 with the corresponding daily climatology on a pixel-by-pixel basis, to determine if values were above the P90 threshold, below the P10 threshold or within the [P10, P90] range. Values above the P90 threshold or below the P10 were flagged as anomalous. The number of anomalous and total valid observations were stored during this process. We then calculated the percentage of valid anomalous observations (above/below the P90/P10 thresholds) for each pixel, to create percentile anomaly maps in terms of % days per year. Finally, we derived an annual indicator map for eutrophication levels: if 25% of the valid observations for a given pixel and year were above the P90 threshold, the pixel was flagged as eutrophic. Similarly, if 25% of the observations for a given pixel were below the P10 threshold, the pixel was flagged as oligotrophic. '''CONTEXT''' Eutrophication is the process by which an excess of nutrients – mainly phosphorus and nitrogen – in a water body leads to increased growth of plant material in an aquatic body. Anthropogenic activities, such as farming, agriculture, aquaculture and industry, are the main source of nutrient input in problem areas (Jickells, 1998; Schindler, 2006; Galloway et al., 2008). Eutrophication is an issue particularly in coastal regions and areas with restricted water flow, such as lakes and rivers (Howarth and Marino, 2006; Smith, 2003). The impact of eutrophication on aquatic ecosystems is well known: nutrient availability boosts plant growth – particularly algal blooms – resulting in a decrease in water quality (Anderson et al., 2002; Howarth et al.; 2000). This can, in turn, cause death by hypoxia of aquatic organisms (Breitburg et al., 2018), ultimately driving changes in community composition (Van Meerssche et al., 2019). Eutrophication has also been linked to changes in the pH (Cai et al., 2011, Wallace et al. 2014) and depletion of inorganic carbon in the aquatic environment (Balmer and Downing, 2011). Oligotrophication is the opposite of eutrophication, where reduction in some limiting resource leads to a decrease in photosynthesis by aquatic plants, reducing the capacity of the ecosystem to sustain the higher organisms in it. Eutrophication is one of the more long-lasting water quality problems in Europe (OSPAR ICG-EUT, 2017), and is on the forefront of most European Directives on water-protection. Efforts to reduce anthropogenically-induced pollution resulted in the implementation of the Water Framework Directive (WFD) in 2000. '''CMEMS KEY FINDINGS''' The coastal and shelf waters, especially between 30 and 400N that showed active oligotrophication flags for 2020 have reduced in 2021 and a reversal to eutrophic flags can be seen in places. Again, the eutrophication index is positive only for a small number of coastal locations just north of 40oN in 2021, however south of 40oN there has been a significant increase in eutrophic flags, particularly around the Azores. In general, the 2021 indicator map showed an increase in oligotrophic areas in the Northern Atlantic and an increase in eutrophic areas in the Southern Atlantic. The Third Integrated Report on the Eutrophication Status of the OSPAR Maritime Area (OSPAR ICG-EUT, 2017) reported an improvement from 2008 to 2017 in eutrophication status across offshore and outer coastal waters of the Greater North Sea, with a decrease in the size of coastal problem areas in Denmark, France, Germany, Ireland, Norway and the United Kingdom. '''DOI (product):''' https://doi.org/10.48670/moi-00195

This visualization product displays plastic bags density per trawl. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during fishing bottom trawl surveys. In cases where the wingspread and/or number of items were unknown, data could not be used because these fields are needed to calculate the density. Data collected before 2011 are affected by this filter. When the distance reported in the data was null, it was calculated from: - the ground speed and the haul duration using this formula: Distance (km) = Haul duration (h) * Ground speed (km/h); - the trawl coordinates if the ground speed and the haul duration were not filled in. The swept area is calculated from the wingspread (which depends on the fishing gear type) and the distance trawled: Swept area (km²) = Distance (km) * Wingspread (km) Densities have been calculated on each trawl and year using the following computation: Density of plastic bags (number of items per km²) = ∑Number of plastic bags related items / Swept area (km²) Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years. The list of selected items for this product is attached to this metadata. Information on data processing and calculation is detailed in the attached methodology document. Warning: the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the Marine Litter Database for this area.

This map presents all layers corresponding to "Marine fishing" activities in the Atlantic area. For more information about this NACE code : https://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=DSP_NOM_DTL_VIEW&StrNom=NACE_REV2&StrLanguageCode=EN&IntPcKey=18495674&IntKey=18495704&StrLayoutCode=HIERARCHIC&IntCurrentPage=1 Indicators collected are : Business indicators per country Number of persons employed on Atlantic pits and rigs Overall gas volume produced Overall volume produced from Atlantic gas terminals

NOAA produces two lines of gridded 0.02deg super-collated L3S LEO SST datasets from Low Earth Orbiting (LEO) satellites, one from the NOAA afternoon JPSS (L3S_LEO_PM) and the other from the EUMETSAT mid-morning Metop-FG (L3S_LEO_AM). The L3S_LEO_AM is derived from Metop-A, -B and -C. The Metop-FG satellite program was jointly established by ESA and EUMETSAT. The US NOAA, under the Initial Joint Polar System Agreement with EUMETSAT, has contributed three AVHRR sensors capable of collecting and transmitting data in the Full Resolution Area Coverage (FRAC; 1km/nadir) format. The L3S_LEO_AM dataset is produced by aggregating three L3U datasets from MetOp-FG satellites ( http://doi.org/10.5067/GHMTA-3US28 , http://doi.org/10.5067/GHMTB-3US28 , http://doi.org/10.5067/GHMTC-3US28 ) and covers from Dec 2006-present. The L3S-LEO-AM data are reported in two files per 24hr interval, one daytime and one nighttime (nominal Metop local equator crossing times around 09:30/21:30, respectively), in NetCDF4 format, compliant with the GHRSST Data Specification version 2 (GDS2). The Near-Real Time (NRT) L3S-LEO data are archived at PO.DAAC with approximately 6 hours latency and then replaced by the Delayed Mode files about 2 months later, with identical file names. The NRT/DM data are seamlessly stitched with the full-mission Reanalysis (RAN). In addition to SST, the L3S-LEO files report the location and intensity of thermal fronts. The ACSPO L3S products are monitored and validated against in situ data in the NOAA iQuam system ( https://www.star.nesdis.noaa.gov/socd/sst/iquam ) in the NOAA SQUAM system ( https://www.star.nesdis.noaa.gov/socd/sst/squam ). Quality of SST imagery and clear-sky mask is evaluated in the NOAA ARMS system ( https://www.star.nesdis.noaa.gov/socd/sst/arms ). NOAA plans to include data from other mid-morning platforms and sensors, such as Metop-SG METImage, into L3S_LEO_AM.

'''Short description:''' The Mean Dynamic Topography MDT-CMEMS_2020_MED is an estimate of the mean over the 1993-2012 period of the sea surface height above geoid for the Mediterranean Sea. This is consistent with the reference time period also used in the SSALTO DUACS products '''DOI (product) :''' https://doi.org/10.48670/moi-00151

This visualization product displays the fishing & aquaculture related plastic items abundance of marine macro-litter (> 2.5cm) per beach per year from non-MSFD monitoring surveys, research & cleaning operations. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols and reference lists used on a European scale. Preliminary processing were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of surveys from non-MSFD monitoring, cleaning and research operations; - Exclusion of beaches without coordinates; - Selection of fishing and aquaculture related plastic items only. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines and EU Threshold Value for Macro Litter on Coastlines from JRC (these two documents are attached to this metadata); - Exclusion of surveys without associated length; - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of fishing & aquaculture related plastic items of the survey (normalized by 100 m) = Number of fishing & aquaculture related items of the survey x (100 / survey length) Then, this normalized number of fishing & aquaculture related plastic items is summed to obtain the total normalized number of fishing & aquaculture related plastic items for each survey. Finally, the median abundance of fishing & aquaculture related plastic items for each beach and year is calculated from these normalized abundances of fishing & aquaculture related items per survey. Percentiles 50, 75, 95 & 99 have been calculated taking into account fishing & aquaculture related plastic items from other sources data for all years. More information is available in the attached documents. Warning: the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the Marine Litter Database for this area.

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). This regional aggregated dataset contains all unrestricted EMODnet Chemistry data on contaminants; temperature, salinity and additional sampling parameters are included when available. The spatial coverage is the Mediterranean Sea with 10917 CDI records divided per matrices: 3095 water profiles and 1385 water timeseries, 1511 sediment profiles and 4083 sediment timeseries, 42 biota profiles and 801 biota timeseries. In the water datasets, the vertical profiles temporal range is from 1974-09-12 to 2015-12-11 and the timeseries temporal range is from 2006-08-17 to 2018-04-26. In the sediment datasets, vertical profiles temporal range is from 1971-01-12 to 2016-04-07 and time series temporal range is from 1981-06-27 to 2018-12-14. For the biota datasets, vertical profiles temporal range is from 2008-05-05 to 2013-05-22 and time series temporal range is from 1979-03-29 to 2017-03-15. Data were harmonised and quality controlled by ‘Hellenic Centre for Marine Research, Hellenic National Oceanographic Data Centre (HCMR/HNODC)’ from Greece. Regional datasets concerning contaminants are automatically harvested. Parameter names in these datasets are based on P01, BODC Parameter Usage Vocabulary, which is available at: https://vocab.seadatanet.org/p01-facet-search. Each measurement value has a quality flag indicator. The resulting data collections for each Sea Basin are harmonised, and the collections are quality controlled by EMODnet Chemistry Regional Leaders using ODV Software and following a common methodology for all Sea Regions. Harmonisation means that: (1) unit conversion is carried out to express contaminant concentrations with a limited set of measurement units (according to EU directives 2013/39/UE; Comm. Dec. EU 2017/848) and (2) merging of variables described by different “local names” ,but corresponding exactly to the same concepts in BODC P01 vocabulary. Detailed documentation is available at: https://doi.org/10.6092/8b52e8d7-dc92-4305-9337-7634a5cae3f4 Explore and extract data at: https://emodnet-chemistry.webodv.awi.de/contaminants%3EMediterranean The harmonised dataset can also be downloaded as ODV spreadsheet (TXT file), which is composed of metadata header followed by tab separated values. This worksheet can be imported to ODV Software for visualisation (More information can be found at: https://www.seadatanet.org/Software/ODV ). The same dataset is offered also as TXT file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms in subcomponents (measure, substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications users (e.g. LibreOffice Calc). The original datasets can be searched and downloaded from EMODnet Chemistry Chemistry CDI Data and Discovery Access Service: https://emodnet-chemistry.maris.nl/search

NOAA STAR produces two lines of gridded 0.02deg super-collated L3S LEO datasets from Low Earth Orbiting (LEO) satellites, one from the NOAA afternoon JPSS (L3S_LEO_PM) and the other from the EUMETSAT mid-morning Metop-FG (L3S_LEO_AM). The L3S_LEO_PM is derived from JPSS satellites (in v2.80, NPP and N20) with VIIRS sensor onboard (0.75km/nadir). The L3S_LEO_PM dataset is produced by aggregating L3U datasets from two JPSS satellites ( https://doi.org/10.5067/GHVRS-3UO28 and https://doi.org/10.5067/GHV20-3UO28 ) and covers from Feb 2012-present. The L3S-LEO-PM data are reported in two files per 24hr interval, one daytime and one nighttime (nominal JPSS local equator crossing times around 01:30/13:30). Data is in NetCDF4 format, compliant with the GHRSST Data Specification version 2 (GDS2). The Near-Real Time (NRT) L3S-LEO data are archived at PO.DAAC with approximately 6 hours latency and then replaced by the Delayed Mode files about 2 months later, with identical file names. In addition to SST, the L3S-LEO files report the location and intensity of thermal fronts. The NRT/DM data are seamlessly stitched with the full-mission Reanalysis (RAN). The ACSPO L3S products are monitored and validated against in situ data in the NOAA iQuam system ( https://www.star.nesdis.noaa.gov/socd/sst/iquam ) in the NOAA SQUAM system ( https://www.star.nesdis.noaa.gov/socd/sst/squam ). Quality of SST imagery, clear-sky mask and thermal fronts is evaluated in the NOAA ARMS system ( https://www.star.nesdis.noaa.gov/socd/sst/arms ). NOAA plans to include data from other afternoon platforms and sensors, such as N21 and Aqua MODIS, into the future releases of the L3S_LEO_PM.

Seasonal Climatology of Chlorophyll-a for Loire River for the period 1976-2020 and for the following seasons: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December Observational data span from 1976 to 2020. Depth levels (m): -125.0, -100.0, -75.0, -50.0,-40.0, -30.0, -25.0, -20.0, -15.0, -10.0, -8.0, -6.0, -4.0, -2.0, -0.0 Data Sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVAnd analysis: The computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.4, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is 0.01 degrees. Correlation length was optimized and filtered vertically and a seasonally-averaged profile was used. Signal to noise ratio was fixed to 1 for vertical profiles and to 0.1 for time series to account for the redundancy in the time series observations. Logarithmic transformation applied to the data prior to the analysis. Background field: the data mean value is subtracted from the data. . Detrending of data: no, Advection constraint applied: no. Units: mg/m^3.

DNA sequencing of Crassostrea gigas Pacific oyster spat infected in the wild with OsHV-1 virus in 4 French oyster basins (Marennes Oleron Bay, Arcachon bay, Rade de Brest and Thau lagoon).